Agentic AI: strategic impact on ticket management

Use case: Ticket management

Unstructured

2 days
(16 hours)
  • Requests come in through scattered channels
  • No categorization or prioritization
  • Rework and loss of context
50 %

Structured

1 day
(8 hours)
  • Standardized intake forms
  • Centralized information
  • Visibility into ticket status
50 %

Automated

4 hours
(4 hours)
  • Automatic ticket classification
  • Suggested initial resolution
  • Automatic progress notifications
70 %

Agentic

Minutes
  • Intelligent complexity analysis
  • Automatic SLA definition
  • Autonomous flow through resolution

Meet the AI Agent powering your ticket management process

Artificial intelligence to reduce SLAs, eliminate manual triage, and add context to decisions.

Request Validation Agent

Automatically analyzes each incoming ticket, validates the information, sets priority and complexity, and guides the workflow through completion—reducing manual effort and response time.

Automated activities:

  • Analyzing the request content and context
  • Automatic definition of priority, complexity, and SLA
  • Structured logging of the rationale for decision and approval

See how Pipefy turns ticket management into an intelligent workflow.

Stage
Pain points
Automated activities
AI Agents
Validation and prioritization

Pain points

Tickets come in with unclear urgency

Manual, subjective prioritization

No criteria for SLA definition

Automated activities

Automatic analysis of the ticket description

Assessment of urgency and complexity

Initial definition of priority and deadline

Handling and execution

Pain points

Time lost understanding the problem

Execution without clear direction

Lack of structured history

Automated activities

Suggested routing or resolution

Structured logging of AI analysis

Automatic deadline updates

Request Validation Agent
Approval stage

Pain points

Slow approvals

Lack of context for decision-making

Back-and-forth between teams

Automated activities

Automatic routing of the ticket for approval

Display of AI rationale

Automatic notifications to owners

Done

Pain points

Lack of visibility into resolved tickets

No history for future analysis

Automated activities

Automatic ticket closure

Logging total resolution time

Final communication to the requester

Up to 40% faster ticket resolution

Reduce SLAs with automatic validation, intelligent prioritization, and less manual rework.

Automatic prioritization from intake

Every ticket enters the workflow already categorized by urgency and complexity.

Less operational rework for support

AI-documented analyses and decisions reduce reopenings and internal back-and-forth.

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